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Nonparametric Dynamic Conditional Beta

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  • Maheu, John M
  • Shamsi, Azam

Abstract

This paper derives a dynamic conditional beta representation using a Bayesian semiparametric multivariate GARCH model. The conditional joint distribution of excess stock returns and market excess returns are modeled as a countably infinite mixture of normals. This allows for deviations from the elliptic family of distributions. Empirically we find the time-varying beta of a stock nonlinearly depends on the contemporaneous value of excess market returns. In highly volatile markets, beta is almost constant, while in stable markets, the beta coefficient can depend asymmetrically on the market excess return. The model is extended to allow nonlinear dependence in Fama-French factors.

Suggested Citation

  • Maheu, John M & Shamsi, Azam, 2016. "Nonparametric Dynamic Conditional Beta," MPRA Paper 73764, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:73764
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    References listed on IDEAS

    as
    1. Jensen, Mark J. & Maheu, John M., 2013. "Bayesian semiparametric multivariate GARCH modeling," Journal of Econometrics, Elsevier, vol. 176(1), pages 3-17.
    2. Bauwens, Luc & Lubrano, Michel & Richard, Jean-Francois, 2000. "Bayesian Inference in Dynamic Econometric Models," OUP Catalogue, Oxford University Press, number 9780198773139.
    3. Engle, Robert F & Ng, Victor K, 1993. "Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
    4. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-131, February.
    5. K. Giannopoulos, 1995. "Estimating the time Varying Components of international stock markets' risk," The European Journal of Finance, Taylor & Francis Journals, vol. 1(2), pages 129-164.
    6. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    7. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    8. Choudhry, Taufiq, 2002. "The Stochastic Structure of the Time-Varying Beta: Evidence from UK Companies," Manchester School, University of Manchester, vol. 70(6), pages 768-791, December.
    9. McCurdy, Thomas H & Morgan, Ieuan, 1992. "Evidence of Risk Premiums in Foreign Currency Futures Markets," The Review of Financial Studies, Society for Financial Studies, vol. 5(1), pages 65-83.
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    Cited by:

    1. Darolles, Serge & Francq, Christian & Laurent, Sébastien, 2018. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," Journal of Econometrics, Elsevier, vol. 204(2), pages 223-247.
    2. Li, Chenxing, 2022. "A multivariate GARCH model with an infinite hidden Markov mixture," MPRA Paper 112792, University Library of Munich, Germany.

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    More about this item

    Keywords

    GARCH; Dirichlet process mixture; slice sampling;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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